
!pip install geopandas


import numpy as np
import pandas as pd
import geopandas as gpd
import folium
import datetime
from IPython.display import HTML, display


fp = '/content/query.csv'
eartt=pd.read_csv(fp)
eartt.head()


eartt1=eartt.rename({'time':'time_hour'}, axis=1)
eartt1.head()


type(eartt1.loc[0,'time_hour'])


eartt1['time_hour']=eartt1['time_hour'].str[:-5]
eartt1['time_hour']=pd.to_datetime(eartt1['time_hour'])


eartt1=eartt1.set_index('time_hour')
eartt1['type']= 'ss'
eartt1.head(1)


start = eartt1.pivot_table('id',
                          index = ['place', 'time_hour',
                                   'latitude',
                                   'longitude', 
                                   'mag'
                                   ],
                          columns = 'type',
                          aggfunc='count').reset_index()




start.head()


start['time_hour']=pd.to_datetime(start['time_hour'])
start['time_hh']=start['time_hour'].dt.hour
start.head()


start.loc[start['mag']<7, 'fillcolor']='#3352FF ' # Earthquakes with magnitude less than 7  = blue color
start.loc[start['mag']>=7, 'fillcolor']='#FF33EC' # Earthquakes with magnitude bigger or equal than 7  = pink color
start.loc[start['mag']>=8, 'fillcolor']='#FCFF33' # Earthquakes with magnitude bigger or equal than 8  = yellow color
start.loc[start['mag']>=9, 'fillcolor']='#FF334C' # Earthquakes with magnitude bigger or equal than 9  = red color


start.shape


start.head()


start['mag']= (start['mag'] - start['mag'].min())/(start['mag'].max()-start['mag'].min())
#df["A"] = (df["A"]-df["A"].min()) / (df["A"].max()-df["A"].min())
start['mag'].head()


def create_geojson_features(df):
    features = []
    
    for _, row in df.iterrows():
        feature = {
            'type': 'Feature',
            'geometry': {
                'type':'Point', 
                'coordinates':[row['longitude'],row['latitude']]
            },
            'properties': {
                'time': pd.to_datetime(row['time_hh'], unit='h').__str__(),
                'style': {'color' : ''},
                'icon': 'circle',
                'iconstyle':{
                    'fillColor': row['fillcolor'],
                    'fillOpacity': 0.8,
                    'stroke': 'true',
                    'radius': row['mag']*10
                }
            }
        }
        features.append(feature)
    return features


start_geojson = create_geojson_features(start)
start_geojson[0]


from folium.plugins import TimestampedGeoJson


EQ_map = folium.Map(location = [2, -2],
                    tiles = "CartoDB Positron",
                    zoom_start = 2)


TimestampedGeoJson(start_geojson,
                  period = 'PT1H',
                  duration = 'PT1H',
                  transition_time = 1000,
                  auto_play = True).add_to(EQ_map)

EQ_map


EQ_map.save('EQ_map.html', title='Earthquakes with Magnitude 6 and higher since 1968')

Installing Libraries¶

Importing Libraries¶

Importing the data as Pandas DataFrame¶

Rename the name of the column¶

The time is imported as text (strings)¶

Changing time to datetime¶

Time as the data frame's index¶

Create a new column called "type" to help us in the pivoting¶

list number of earquakes by place, time, location, magnitude¶

Extract the hour from time_hour¶

Choosing color depending on the magnitude for each Earthquake¶

Normalizing magnitude with max and min values¶

Function to create the features of the animation: time, location, icon to represent magnitude of Earthquake, etc¶

Calling the Function create_geojson_features and using it in our data frame and get the geojson¶

Creating Interactive And Animated Map¶